{"title":"Optimal control of diabetes model with the impact of endocrine-disrupting chemical: an emerging increased diabetes risk factor","authors":"P. Logaprakash, C. Moni̇ca","doi":"10.53391/mmnsa.1397575","DOIUrl":null,"url":null,"abstract":"Diabetes, a persistent pathological condition characterized by disruptions in insulin hormone regulation, has exhibited a noteworthy escalation in its prevalence over recent decades. The surge in incidence is notably associated with the proliferation of endocrine-disrupting chemicals (EDCs), which have emerged as primary contributors to the manifestation of insulin resistance and the consequent disruption of beta cell function, ultimately culminating in the onset of diabetes. Consequently, this study endeavors to introduce a model for diabetes that aims to elucidate the ramifications of exposure to EDCs within the diabetic population. In the pursuit of mitigating the deleterious effects of EDC-induced diabetes, we propose a framework for optimal control strategies. The utilization of Pontryagin’s maximum principle serves to explicate the principles governing the optimal control mechanisms within the proposed model. Our findings underscore that heightened concentrations of EDCs play a pivotal role in exacerbating the prevalence of diabetes. To substantiate our model, we employ parameter estimation techniques utilizing a diabetes dataset specific to the demographic context of India. This research contributes valuable insights into the imperative need for proactive measures to regulate and diminish EDC exposure, thereby mitigating the escalating diabetes epidemic.","PeriodicalId":210715,"journal":{"name":"Mathematical Modelling and Numerical Simulation with Applications","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Modelling and Numerical Simulation with Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53391/mmnsa.1397575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Diabetes, a persistent pathological condition characterized by disruptions in insulin hormone regulation, has exhibited a noteworthy escalation in its prevalence over recent decades. The surge in incidence is notably associated with the proliferation of endocrine-disrupting chemicals (EDCs), which have emerged as primary contributors to the manifestation of insulin resistance and the consequent disruption of beta cell function, ultimately culminating in the onset of diabetes. Consequently, this study endeavors to introduce a model for diabetes that aims to elucidate the ramifications of exposure to EDCs within the diabetic population. In the pursuit of mitigating the deleterious effects of EDC-induced diabetes, we propose a framework for optimal control strategies. The utilization of Pontryagin’s maximum principle serves to explicate the principles governing the optimal control mechanisms within the proposed model. Our findings underscore that heightened concentrations of EDCs play a pivotal role in exacerbating the prevalence of diabetes. To substantiate our model, we employ parameter estimation techniques utilizing a diabetes dataset specific to the demographic context of India. This research contributes valuable insights into the imperative need for proactive measures to regulate and diminish EDC exposure, thereby mitigating the escalating diabetes epidemic.
糖尿病是一种以胰岛素激素调节紊乱为特征的顽固性病症,近几十年来,其发病率显著上升。发病率的激增主要与干扰内分泌的化学物质(EDCs)的激增有关,这些化学物质已成为导致胰岛素抵抗和随之而来的β细胞功能紊乱的主要因素,最终导致糖尿病的发生。因此,本研究试图引入一种糖尿病模型,旨在阐明糖尿病人群暴露于 EDCs 的影响。为了减轻 EDC 引发的糖尿病的有害影响,我们提出了一个最佳控制策略框架。庞特里亚金最大原则的使用有助于解释拟议模型中最优控制机制的原理。我们的研究结果表明,EDCs 浓度的升高在加剧糖尿病患病率方面起着关键作用。为了证实我们的模型,我们利用针对印度人口背景的糖尿病数据集,采用了参数估计技术。这项研究为我们提供了宝贵的见解,说明我们亟需采取积极主动的措施来调节和减少接触 EDC 的机会,从而缓解不断升级的糖尿病疫情。